Abstract
This paper deals with the study of robustness in genetic algorithms from the viewpoint of population diversity when dealing with a complex combinatorial optimization problem. In this case, robustness of algorithms for the job shop scheduling problem in the presence of processing time and number of job perturbations is studied. Three different algorithms are compared: a standard genetic algorithm and two selection level diversity control methods. Definitions of robustness and diversity are presented in order to build a framework for the study of their relations. It is concluded in this research that the key to obtaining a robust design is neither accuracy nor diversity but an exigent combination of both.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.